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Empirical forecasting of slow-onset disasters for improved emergency response: An application to Kenya’s arid north

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Title Empirical forecasting of slow-onset disasters for improved emergency response: An application to Kenya’s arid north
 
Creator Mude, Andrew G.
Barrett, Christopher B.
McPeak, J.G.
Kaitho, R.
Kristjanson, Patricia M.
 
Description Andrew G. Mude, Robert Kaitho and Patti Kristjanson are ILRI authors.
Mitigating the negative welfare consequences of crises such as droughts, floods, and disease outbreaks, is a major challenge in many areas of the world, especially in highly vulnerable areas insufficiently equipped to prevent food and livelihood security crisis in the face of adverse shocks. Given the finite resources allocated for emergency response, and the expected increase in incidences of humanitarian catastrophe due to changing climate patterns, there is a need for rigorous and efficient methods of early warning and emergency needs assessment. In this paper we develop an empirical model, based on a relatively parsimonious set of regularly measured variables from communities in Kenya’s arid north, that generates remarkably accurate forecasts of the likelihood of famine with at least 3 months lead time. Such a forecasting model is a potentially valuable tool for enhancing early warning capacity.
 
Date 2010-01-10T11:29:04Z
2010-01-10T11:29:04Z
2009-08-15
 
Type Journal Article
 
Identifier Mude, A.G., Barrett, C.B., McPeak, J.G., Kaitho, R. and Kristjanson, P. 2009. Empirical forecasting of slow-onset disasters for improved emergency response: An application to Kenya’s arid north. Food Policy 34(4):329-339.
https://hdl.handle.net/10568/371
 
Language en
 
Source Food Policy